Proteins are major components of cells and the spatiotemporal expression pattern and the subcellular localization of proteins determine the shape, structure, and function of cells. Many proteins are dynamically regulated so that their activity is altered in response to certain intrinsic or extrinsic cues frequently referred to herein as “activation events”. Such regulation generally occurs in the context of protein-protein interaction networks commonly described as signal transduction cascades. The individual members of such cascades often exist in either active or non-active states, and it is the conversion between these states that leads to propagation or inhibition of a signal through the cascade. Given their integral role in cellular development and function, dysregulation of such cascades can lead to numerous diseases, and in particular those diseases involving improper cell proliferation such as cancer.
Researchers investigating signal transduction cascades have traditionally used methods that rely on lysates of cellular populations, e.g. western blots. Such methods have a number of inherent limitations that can obscure key information. For example, using populations of cells to produce a lysate hightens the possibility that rare cell events will be diluted to an extent that key activation events are no longer evident. In addition, the use of lysates can only approximate the native cellular activation profiles of signal cascades, as lysis inherently alters the cascade environment. Given such limitations, new methods capable of focusing on the indiviual members of signal transduction cascades in native environments are necessary to better understand the role of activation events in disease.
Accordingly, the present invention provides an approach for the simultaneous determination of the activation states of a plurality of proteins in single cells. This approach permits the rapid detection of heterogeneity in a complex cell population based on activation states, and the identification of cellular subsets that exhibit correlated changes in activation within the cell population. Moreover, this approach allows the correlation of cellular activities or properties, including the ability to classify disease states based on signal transduction activation state. In addition, the use of potentiators of cellular activation allows for further characterization of such pathways and cell populations.